Selecting Target Markets, Segments and Accounts
5 min read
Lesson objectives
- Distinguish market, segment, account and contact and use each level for the appropriate decision.
- Build a B2B segment definition using need- and fit-related dimensions.
- Use a weighted scorecard with correct calculation, sensitivity testing and explicit assumptions.
From market to account: different levels of choice
When a team says “we target this market,” it often skips several levels. A market is a broad space of buyers, problems and alternatives; a segment is a group sharing characteristics or needs that make a similar approach useful; a target account is a specific organization whose fit and accessibility we want to assess. A person inside the account is a contact or role, not the market itself. Each level answers a different question; mixing them leads to scattered research and generic outreach.
In B2B markets, segmentation need not rely on one dimension such as size or industry. Relevant dimensions can include firm characteristics, needs, potential value, behavior or buying approach. The key is decision relevance: does the segmentation identify a group that can be served in a differentiated and executable way? If a variable changes nothing about the value proposition, access or economics, it may be descriptive rather than useful for selection.
| Level | Example | Typical decision |
|---|---|---|
| Market | Corporate professional-learning solutions | Is there a problem space worth research? |
| Segment | Mid-sized service firms with distributed teams | Is the need recurrent enough for a shared approach? |
| Account | A specific organization in the segment | Is this account a fit now and worth time? |
| Contact | A learning or operations role inside the account | Who has knowledge of or influence over the problem and decision? |
A prioritization scorecard: a discussion aid, not objective truth
A team can use a weighted scorecard to reduce purely intuitive decisions. In this teaching example, five criteria are rated from 1 to 5: need strength 30%, capability fit 25%, access 20%, preliminary economics 15%, and evidence strength 10%. Score = sum of (criterion rating × weight). These weights are not a universal standard; they are explicit assumptions that should be reviewed. Changing a weight or criterion definition can change the result, so the explanation must stay beside the number.
When selecting accounts, avoid collecting personal data you do not need. Early-stage work can often rely on organization-level information, relevant professional roles, and need signals that are public or voluntarily provided in a legitimate context. The goal is to understand fit, not to build excessive profiles of individuals. Sensitive or decision-irrelevant personal characteristics should not be used as prioritization criteria.
Lesson summary
Good selection defines the decision level, uses meaningful segmentation, and compares opportunities with explicit criteria, sensitivity checks and evidence quality.